Rust Software Engineer - Distributed Systems

Alignerr Corp.; United States; Remote; GBP 96,000 - 165,000; Full time

Job summary

Alignerr is seeking a Senior Rust Engineer to design and optimize high-performance distributed infrastructure powering AI data pipelines, annotation tooling, and evaluation systems. This is a fully remote, hourly contract role for engineers who write production Rust and care about scalable data workflows.

You will collaborate with AI research teams, tackle bottlenecks, and help shape architecture across data collection, validation, and evaluation stages.

Qualifications

• 3–5+ years of professional experience writing production-grade Rust.
• Experience building distributed services using RPC frameworks and distributed state or consensus.
• Debug complex concurrency issues — deadlocks, race conditions — with async instrumentation and tracing tools.
• Clear, precise written and verbal communicator.
• Native or fluent English speaker.
• Available and able to commit 20–40 hours per week.

Responsibilities

• Design, build, and optimize high-performance Rust systems for data pipelines and evaluation workflows.
• Develop full-stack backend services and tooling for large-scale data annotation, validation, and quality control.
• Improve reliability, safety, and performance across existing production Rust codebases.
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows.
• Identify and resolve bottlenecks, edge cases, and systemic issues in distributed data systems.
• Participate in synchronous design reviews and iterate on architecture and implementation decisions.

Skills

Rust production

Distributed services

Concurrency debugging

Communication skills

English fluency

Hours availability

Job description

Senior Rust Engineer — AI Data & Distributed Infrastructure

About The Role

What if your Rust expertise could directly shape the infrastructure powering the next generation of AI? We're looking for a seasoned Rust engineer to build and optimize the high-performance distributed systems that leading AI labs depend on — from data pipelines and annotation tooling to evaluation infrastructure at scale.

This is a fully remote, flexible contract role for engineers who write production Rust, think deeply about distributed systems, and want their work to matter.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

What You'll Do

• Design, build, and optimize high-performance Rust systems that support AI data pipelines and evaluation workflows
• Develop full-stack backend services and tooling for large-scale data annotation, validation, and quality control
• Improve reliability, safety, and performance across existing production Rust codebases
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Identify and resolve bottlenecks, edge cases, and systemic issues in distributed data systems
• Participate in synchronous design reviews and iterate on architecture and implementation decisions

Who You Are

• 3–5+ years of professional experience writing production-grade Rust
• Strong background building distributed services using RPC frameworks and managing distributed state or consensus
• Experienced debugging complex concurrency issues — deadlocks, race conditions — using async instrumentation and tracing tools
• Clear, precise written and verbal communicator — you can articulate technical decisions to a mixed audience
• Native or fluent English speaker
• Available and able to commit 20–40 hours per week

Nice to Have

• Prior experience with data annotation, data quality pipelines, or model evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
• Background in developer tooling or platform engineering

Why Join Us

• Work on real production systems used by leading AI research labs — not toy projects
• Fully remote and async-friendly — work from wherever you do your best thinking
• Freelance autonomy with the structure of meaningful, high-stakes engineering work
• Tackle genuinely hard technical problems at the intersection of systems engineering and AI
• Potential for ongoing engagement and expanded scope as projects evolve